First, let’s go over the paper at a very high level. In order to facilitate legal research, legal publishers like LexisNexis and West tag cases from their available ontology of legal concepts. These headnotes are very helpful, especially when dealing with "multi-dimensional" cases where the Court may address (or argue why it should not address) more than one legal question. Examples of Lexis’s headnotes include:

Workers’ Compensation & SSDI > Third Party Actions > Third Party Liability

Criminal Law & Procedure>Interrogation

The first thing you should notice is that these headnotes are hierarchical. There are top level categories, like Constitutional Law, Administrative Law, and Criminal Law & Procedure, as well as lower level categories, like Interrogation, Third Party Liability, and Forums. These concepts occur at different levels, and the figure below conveys the overall structure of this concept hierarchy. There are 42 separate top level head notes, 603 second level headnotes, and many more below.

Since 42 headnotes is probably too little categorization to say much about a Supreme Court case, let’s focus on second level headnotes. These give us 603 separate, editorially-assigned tags for cases. Each case can have 0 or more of these tags. So how might we procede?

First, let’s look at how often these headnotes co-occur within a case. Co-occurrence can imply a number of things. For example, it might mean that the facts of a case led two separate legal issues to come into question. Alternatively, it might mean that a Justice used analogical reasoning to "import" precedent from one legal concept to another. Regardless of the specific reason, the frequencies of these co-occurrences broadly indicate the level of interaction between legal concepts. To visualize the macro-level structure of these relationships, we can examine the weighted network layout below.

Alternatively, we could look at citation instead of co-occurrence. In this case, we are interested in cases with one headnote that cite a case with another headnote. Like co-occurrence, these citations may imply multiple relationships. For example, just as above, these could indicate instances of "concept importation" where precedent from one domain is applied to another. The weighted network visual below displays the resulting citation relationships among headnotes.

These visuals are interesting, but how could we use these ideas to ask specific legal questions? As a case study, let’s try to trace the history of criminal suspect rights such as those discussed in Miranda v. Arizona. Let’s say that we are particularly interested in how the Bill of Rights was used in discussion of criminal interrogation. The standard research approach might look like this:

Determine a set of terms or phrases that correspond to discussion of the Bill of Rights

Determine a set of terms or phrases that correspond to discussion of criminal interrogation

Combine these in a query to Lexis or West.

Reverse sort by date

Examine each case to determine whether your query did a good job.

Adjust query and repeat 1-6 until happy.

With headnotes, however, we can simply count the number of cases where the Bill of Rights headnote and the Interrogation headnote co-occur. The first case that matches this logic is Hopt v. People of the Territory of Utah, 110 U.S. 574.

Elementary writers of authority concur in saying that, while from the very nature of such evidence it must be subjected to careful scrutiny and received with great caution, a deliberate, voluntary confession of guilt is among the most effectual proofs in the law, and constitutes the strongest evidence against the party making it that can be given of the facts stated in such confession. 1 Greenleaf Ev. § 215; 1 Archbold Cr. Pl. 125; 1 Phillips’ Ev. 533-34; Starkie Ev. 73.

A time series representation of these co-occurrences in the figure below also gives us meaningful information about these issue over time. While the result may not seem surprising given how much attention has been paid to development of Miranda rights, this technique is equally useful in less-studied domains.

If any of these ideas have seemed interesting, feel free to check out the paper on SSRN. There’s plenty more information and visualization in the paper.

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